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Artificial Intelligence In Data Mining

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Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition Book
Author : Petra Perner
Publisher : Springer Science & Business Media
Release : 2011-08-12
ISBN : 3642231985
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA. The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, application in medicine, webmining and information mining; and machine learning and image mining.

Machine Learning and Data Mining

Machine Learning and Data Mining Book
Author : Igor Kononenko,Matjaz Kukar
Publisher : Elsevier
Release : 2007-04-30
ISBN : 0857099442
Language : En, Es, Fr & De

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Book Description :

Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining. Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining A valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions

Artificial Intelligence and Data Mining Approaches in Security Frameworks

Artificial Intelligence and Data Mining Approaches in Security Frameworks Book
Author : Neeraj Bhargava,Ritu Bhargava,Pramod Singh Rathore,Rashmi Agrawal
Publisher : John Wiley & Sons
Release : 2021-08-11
ISBN : 1119760437
Language : En, Es, Fr & De

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Book Description :

Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to Artificial Intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalize security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and Data Mining and several other computing technologies to deploy such system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library.

Artificial Intelligence in Data Mining

Artificial Intelligence in Data Mining Book
Author : D. Binu,B.R. Rajakumar
Publisher : Academic Press
Release : 2021-02-17
ISBN : 0128206160
Language : En, Es, Fr & De

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Book Description :

Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense

Artificial Intelligence and Data Mining in Healthcare

Artificial Intelligence and Data Mining in Healthcare Book
Author : Malek Masmoudi,Bassem Jarboui,Patrick Siarry
Publisher : Springer Nature
Release : 2021
ISBN : 3030452409
Language : En, Es, Fr & De

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Book Description :

This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition Book
Author : Petra Perner
Publisher : Springer
Release : 2012-07-07
ISBN : 9783642315367
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 8th International Conference, MLDM 2012, held in Berlin, Germany in July 2012. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition Book
Author : Petra Perner
Publisher : Springer
Release : 2018-07-08
ISBN : 9783319961323
Language : En, Es, Fr & De

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Book Description :

This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

2nd INFORMS Workshop on Artificial Intelligence and Data Mining

2nd INFORMS Workshop on Artificial Intelligence and Data Mining Book
Author : Wei Jiang,Anurag Agarwal
Publisher : Unknown
Release : 2009
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download 2nd INFORMS Workshop on Artificial Intelligence and Data Mining book written by Wei Jiang,Anurag Agarwal, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Artificial Intelligence and Data Mining for Mergers and Acquisitions

Artificial Intelligence and Data Mining for Mergers and Acquisitions Book
Author : Debasis Chanda
Publisher : Unknown
Release : 2021
ISBN : 9780367720902
Language : En, Es, Fr & De

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Book Description :

Download Artificial Intelligence and Data Mining for Mergers and Acquisitions book written by Debasis Chanda, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Data Science

Data Science Book
Author : Richard Hurley
Publisher : Unknown
Release : 2019-11-02
ISBN : 9781704636030
Language : En, Es, Fr & De

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Book Description :

If you want to learn about data science and big data, then keep reading... Two manuscripts in one book: Data Science: What You Need to Know About Data Analytics, Data Mining, Regression Analysis, Artificial Intelligence, Big Data for Business, Data Visualization, Database Querying, and Machine Learning Big Data: A Guide to Big Data Trends, Artificial Intelligence, Machine Learning, Predictive Analytics, Internet of Things, Data Science, Data Analytics, Business Intelligence, and Data Mining This book will discuss everything that you need to know when it comes to working in the field of data science. This world has changed, and with the modern technology that we have, it is easier than ever for companies to amass a large amount of data on the industry, on their competition, on their products, and their customers. Gathering the data is the easy part, though. Being able to sort through this data and understand what it is saying is going to be a unique challenge all on its own. This is where the process and field of data science can come in. There is so much that we can explore and learn about when it comes to the world of data science, and this ultimate guide is here to help you navigate through these specialties. You will see just how important the ideas of data mining, data analytics, and even artificial intelligence are to our world as a whole today. Some of the topics covered in part 1 of this book include: What is Data Science? What Exactly Does a Data Scientist Do? A Look at What Data Analytics Is All About What is Data Mining and How Does It Fit in with Data Science? Regression Analysis Why is Data Visualization So Important When It Comes to Understanding Your Data? How to work with Database Querying A Look at Artificial Intelligence What is Machine Learning and How Is It Different from Artificial Intelligence? What is the Future of Artificial Intelligence and Machine Learning? And much more! Some of the topics covered in part 2 of this book include: What is big data, and why is it important? The five V's behind big data How big data is already impacting your life, and where big data may be headed How big data and your everyday devices and appliances will come together in unexpected ways via the Internet of Things How companies and governments are using predictive analytics to get ahead of the competition or improve service How big data is used for fraud detection How big data can train intelligent computer systems The many ways large corporations are benefiting from big data and the tools that use it like machine learning, AI, and predictive analytics Upcoming trends in big data that are sure to have a large impact on your future Artificial intelligence, and how big data drives its development What machine learning is and how it is tied to big data The relationship between big data, data analytics, and business intelligence Insights into how big data impacts privacy issues The pros and cons regarding big data And much, much more! So if you want to learn more about data science and big data, click the "add to cart" button!

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition Book
Author : Petra Perner
Publisher : Springer Science & Business Media
Release : 2009-07-21
ISBN : 364203070X
Language : En, Es, Fr & De

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Book Description :

There is no royal road to science, and only those who do not dread the fatiguing climb of its steep paths have a chance of gaining its luminous summits. Karl Marx A Universial Genius of the 19th Century Many scientists from all over the world during the past two years since the MLDM 2007 have come along on the stony way to the sunny summit of science and have worked hard on new ideas and applications in the area of data mining in pattern r- ognition. Our thanks go to all those who took part in this year's MLDM. We appre- ate their submissions and the ideas shared with the Program Committee. We received over 205 submissions from all over the world to the International Conference on - chine Learning and Data Mining, MLDM 2009. The Program Committee carefully selected the best papers for this year’s program and gave detailed comments on each submitted paper. There were 63 papers selected for oral presentation and 17 papers for poster presentation. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data-mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining. Among these topics this year were special contributions to subtopics such as attribute discre- zation and data preparation, novelty and outlier detection, and distances and simila- ties.

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition Book
Author : Petra Perner
Publisher : Springer
Release : 2017-07-04
ISBN : 9783319624150
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully reviewed and selected from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Data Mining Know It All

Data Mining  Know It All Book
Author : Soumen Chakrabarti,Earl Cox,Eibe Frank,Ralf Hartmut Güting,Jiawei Han,Xia Jiang,Micheline Kamber,Sam S. Lightstone,Thomas P. Nadeau,Richard E. Neapolitan,Dorian Pyle,Mamdouh Refaat,Markus Schneider,Toby J. Teorey,Ian H. Witten
Publisher : Morgan Kaufmann
Release : 2008-10-31
ISBN : 9780080877884
Language : En, Es, Fr & De

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Book Description :

This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology. The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining. This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources. Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints. Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader’s technical expertise and ability to implement practical solutions. Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases.

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining Book
Author : Hady W. Lauw,Raymond Chi-Wing Wong,Alexandros Ntoulas,Ee-Peng Lim,See-Kiong Ng,Sinno Jialin Pan
Publisher : Springer Nature
Release : 2020
ISBN : 3030474267
Language : En, Es, Fr & De

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Book Description :

The two-volume set LNAI 12084 and 12085 constitutes the thoroughly refereed proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, which was due to be held in Singapore, in May 2020. The conference was held virtually due to the COVID-19 pandemic. The 135 full papers presented were carefully reviewed and selected from 628 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: recommender systems; classification; clustering; mining social networks; representation learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors in data mining; mining sequential data; mining imbalanced data; association; privacy and security; supervised learning; novel algorithms; mining multi-media/multi-dimensional data; application; mining graph and network data; anomaly detection and analytics; mining spatial, temporal, unstructured and semi-structured data; sentiment analysis; statistical/graphical model; multi-source/distributed/parallel/cloud computing.

MACHINE LEARNING

MACHINE LEARNING Book
Author : Mulayam Singh
Publisher : BookRix
Release : 2020-05-29
ISBN : 3748743572
Language : En, Es, Fr & De

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Book Description :

The Evolution of Data Science and the Information Age. Data science is a large vast time period that encompasses a variety of disciplines and standards which includes big data, Artificial Intelligence (AI), data mining and machine learning. The self-discipline of analyzing giant volumes of data recognized as 'data science', is relatively new and has grown hand-in-hand with the improvement and widespread adoption of computers. Prior to computers, records used to be calculated and processed by hand underneath the umbrella of 'statistics' or what we would possibly now refer to as 'classical statistics'. Baseball batting averages, for example, existed properly earlier than the creation of computers. Anyone with a pencil, notepad and primary arithmetic abilities could calculate Babe Ruth's batting common over a season with the useful resource of classical statistics. The method of calculating a batting common concerned the dedication of time to accumulate and assessment batting sheets, and the software of addition and division. The key factor to make about classical data is that you don't strictly need a laptop to work the statistics and draw new insight. As you're working with small facts units it is feasible to even for pre-university college students to conduct statistics. Indeed data is nevertheless taught in colleges today, and as they have been for centuries. In this book you will learn all about machine learning and data mining. Hope you will love this book.

Machine Learning and Data Mining MLDM in Pattern Recognition

Machine Learning and Data Mining MLDM in Pattern Recognition Book
Author : Petra Perner,MLDM,Uwe Zscherpel
Publisher : Unknown
Release : 2002
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Machine Learning and Data Mining MLDM in Pattern Recognition book written by Petra Perner,MLDM,Uwe Zscherpel, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Data Mining for Business Applications

Data Mining for Business Applications Book
Author : Carlos A. Mota Soares,Rayid Ghani
Publisher : IOS Press
Release : 2010-01-01
ISBN : 1607506327
Language : En, Es, Fr & De

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Book Description :

Data mining is already incorporated into the business processes in sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This book contains extended versions of a selection of papers presented at a series of workshops held between 2005 and 2008 on the subject of data mining for business applications.

Nature Inspired Computation in Data Mining and Machine Learning

Nature Inspired Computation in Data Mining and Machine Learning Book
Author : Xin-She Yang,Xing-Shi He
Publisher : Springer Nature
Release : 2019-09-03
ISBN : 3030285537
Language : En, Es, Fr & De

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Book Description :

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.

Data Preparation for Data Mining

Data Preparation for Data Mining Book
Author : Dorian Pyle
Publisher : Morgan Kaufmann
Release : 1999-04-05
ISBN : 9781558605299
Language : En, Es, Fr & De

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Book Description :

Data Preparation for Data Mining addresses an issue unfortunately ignored by most authorities on data mining: data preparation. Thanks largely to its perceived difficulty, data preparation has traditionally taken a backseat to the more alluring question of how best to extract meaningful knowledge. But without adequate preparation of your data, the return on the resources invested in mining is certain to be disappointing. Dorian Pyle corrects this imbalance. A twenty-five-year veteran of what has become the data mining industry, Pyle shares his own successful data preparation methodology, offering both a conceptual overview for managers and complete technical details for IT professionals. Apply his techniques and watch your mining efforts pay off-in the form of improved performance, reduced distortion, and more valuable results. On the enclosed CD-ROM, you'll find a suite of programs as C source code and compiled into a command-line-driven toolkit. This code illustrates how the author's techniques can be applied to arrive at an automated preparation solution that works for you. Also included are demonstration versions of three commercial products that help with data preparation, along with sample data with which you can practice and experiment. * Offers in-depth coverage of an essential but largely ignored subject. * Goes far beyond theory, leading you-step by step-through the author's own data preparation techniques. * Provides practical illustrations of the author's methodology using realistic sample data sets. * Includes algorithms you can apply directly to your own project, along with instructions for understanding when automation is possible and when greater intervention is required. * Explains how to identify and correct data problems that may be present in your application. * Prepares miners, helping them head into preparation with a better understanding of data sets and their limitations.

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition Book
Author : Petra Perner
Publisher : Springer
Release : 2015-07-13
ISBN : 9783319210230
Language : En, Es, Fr & De

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Book Description :

This book constitutes the refereed proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2015, held in Hamburg, Germany in July 2015. The 41 full papers presented were carefully reviewed and selected from 123 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.